2026-06-10 –, WS Room 2418
In this Unconference session, we seek to discuss ways to facilitate more interdisciplinary research collaboration, which is largely promoted as beneficial but comes with limited structural support to do so. As a starting point for discussion, we will present a free app developed to foster research collaboration: ResearchRendezvous. Traditional methods of academic networking are ineffective and inefficient, with no streamlined methods of sharing budding research ideas and finding collaborators to help bring ideas to life. Our app allows users at conferences and beyond to quickly search through others’ research ideas, find ones they are interested in collaborating on, and open a chat to establish lines of communication – much like a dating app, but for research ideas! Participants will get the chance to pilot test the app during this session, discuss its use potential, give feedback on how to improve the app, and discuss additional ideas to facilitate interdisciplinary collaboration.
Esther Wong
Please classify your session as the theme it fits best in:: Incentives/Culture - Content related to the incentive structure of science, culture, and norms of science How will the session's content foster diversity & inclusion (e.g., who will present, who will it serve), and how will it improve psychological science?:The session has a goal of facilitating interdisciplinary collaboration and fostering better inclusion of researchers from diverse backgrounds. It will present a tangible beta test phone app that can be used and tested for facilitating research collaboration during the conference.
Please note any pre-requisite knowledge/expertise you will expect from attendees (i.e., is the session most appropriate for someone who already has experience with a topic?).:No prior experience is needed
Steven Zhou is an Assistant Professor of Psychological Science at Claremont McKenna College. His research and teaching focus on quantitative methods and data science applied to organizational phenomena such as leadership, personality, and career development. He uses methods ranging from traditional multivariate statistics to natural language processing (NLP) and AI, with an eye toward producing research with real-world impact for everyday leaders, managers, and employees. He earned his Ph.D. in Organizational Psychology from George Mason University with a certificate in Computational Social Sciences. He has previous industry work experience in HR, nonprofit management, and institutional data analytics.